"Advances in Memristor Neural Networks: Modeling and Applications" ed. by Calin Ciufudean

This book deals with advanced applications illustrating these concepts, and delivers an important contribution for the achievement of the next generation of intelligent hybrid biostructures. Different modeling and simulation tools can deliver an alternative to funding the theoretical approach as well as practical implementation of memristive systems.

Nowadays, scientific research deals with alternative solutions for creating non-traditional computing systems, such as neural network architectures where the stochastic nature and live dynamics of memristive models play a key role. The features of memristors make it possible to direct processing and analysis of both biosystems and systems driven by artificial intelligence, as well as develop plausible physical models of spiking neural networks with self-organization.

Contents
1. Synaptic Behavior in Metal Oxide-Based Memristors
2. The Roadmap to Realize Memristive Three-Dimensional Neuromorphic Computing System
3. Memristive Anodic Oxides: Production, Properties and Applications in Neuromorphic Computing
4. Memristive Systems Based on Two-Dimensional Materials
5. Charge-Controlled Memristor Grid for Edge Detection


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